Before Christmas I started writing
about the issue of mine planning. This entry follows that same
theme. This week, I will again visit the area of mine plans not
delivering quality information for appropriate decision making. Why
haven’t shareholders and the stock exchanges held Boards of Directors
accountable for their poor decisions on how to proceed with mining a particular
resource or whether to proceed at all. When shareholders and stock
exchanges start holding mining companies accountable for the decisions they
make, the people doing the planning might need to start explaining
themselves. Development engineers may need to dust off their CV’s and
mine planning consultants might need to become acquainted with their
Professional Indemnity insurers.
The scheduling side of Mine
Planning Tools is letting the industry down badly. As new logging and
monitoring technologies are being developed, the amount of and complexity of
the data is becoming overwhelming and decisions are often made based on only a
small portion of the available data. In most cases production estimates
are higher than what is achieved. Is it a human trait to be optimistic or
is it pressure to produce results which are good enough to gain shareholder or
Executive Management approval? We work in an industry which is wildly
optimistic about what could be achieved and then prepared to accept mediocrity
in what is delivered.
Most of the inputs are based on
‘ideal’ values or values that are given by OEM’s or third party
experts. The biggest mistake made by planners and their managers is
not linking the detail of the plan to the requirement of the stage of
planning. A good example is a long term plan which plans a shovel or
excavator down to payload, wait on truck, fill time, swing time, etc. and then
ties it all together in some impressive-looking Monte Carlo simulation.
Surely for a long term plan you should use realistic annual production
numbers. Detailed analysis follows. Then we have the problems with
planners not using enough detail for short term plans. Now this is a fine
line. We can collect data ad nauseum but then something changes in the
pit so the ongoing optimisation of the plan becomes a balance between
collecting and using data and the dynamics of the pit.
The following are actual
reasons why overly ambitious production rates have been used from personal
experience;
- Dig depths and face heights not
considered,
- Variation in seam dip not
considered,
- Planning done in 2D and then
merged to 3D,
- Scheduling using maximum
potential rate for KPI’s and productivity rather than what can be achieved
over a longer period,
- Scaling performance from
equipment of different capacity,
- Overestimating hours of work,
- Not considering fleet
interactions,
- Not understanding operational
limitations, eg. Double side loading vs single side loading
- Not understanding densities and
bucket fill
While most mining executives
have encountered plans which have gone pear shaped they haven’t always
understood why. Well the answer is in many occasions the poor use of
realistic production rates. The following are actual examples from our
work in the past for loading units and trucks:
- Truck fleet actual operating
hours 21% below plan.
- Electric rope shovel actual
annual output up to 33% below plan.
- BER (payload / bucket capacity)
25% below plan
- Payload for trucks being
assumed at design load, when on-site performance was 14% underloading
(limited by tray volume)
- Dragline swing time used in
plan was 14 seconds when actual time was 22 seconds.
- In 2008 the average shortfall
in dragline coal uncovered was one million tonnes per dragline, (for 20%
of draglines there was a shortfall of over two millions of coal)
In each of these cases (partly
the reason I chose them) the actual performance is not vastly different from
the worldwide average for the make and model.
You can’t plan effectively
without accurate inputs. You can’t make good decisions without good
planning. You don’t have to accept inaccurate inputs. Just use the
data available. Benchmark against industry standards. It seems too
obvious.
Graham Lumley
BE(Min)Hons, MBA, DBA, FAUSIMM(CP), MMICA, MAICD, RPEQ
